Co-Targeting Luminal B Breast Cancer with S-Adenosylmethionine and Immune Checkpoint Inhibitor Reduces Primary Tumor Growth and Progression, and Metastasis to Lungs and Bone
<p>Effect of SAM on proliferation, colony-formation (survival), and invasion of luminal B BCa cell lines. (<b>A</b>) Percentage proliferation (± SEM) relative to control at 1, 2, and 3 days after SAM treatment. Briefly, Eo771 (4 × 10<sup>4</sup>) and R221A (1 × 10<sup>4</sup>) cells were seeded in 6-well plates, treatment with SAM (200 μM) started 2 days after seeding, and they were treated every day for 3 days. Cells were trypsinized and counted 1, 2, and 3 days after SAM treatment. (<b>B</b>) Percentage survival fraction (± SEM) relative to control obtained from soft agar colony formation assay. The colony formation assay was performed after the regular proliferation assay, and then the treated Eo771 (5 × 10<sup>3</sup>) and R221A (5 × 10<sup>3</sup>) cells were plated. Media was replenished every 4–5 days and colonies were counted after 3 weeks. (<b>C</b>) Invasion assay was performed after performing the regular proliferation assay and then incubating the treated cells (1.25 × 10<sup>5</sup>) for 18 h in two-compartment Boyden chambers coated with Matrigel. Top: Percentage invasion (± SEM) relative to control. Bottom: Representative images (lens, 40×; magnification, 400×) of invaded cells. Results are the mean of at least three independent experiments. Statistical significance was determined by (<b>A</b>) two-way ANOVA and (<b>B</b>, <b>C</b>) T-test in GraphPad prism. Significance values are represented by asterisks (*** <span class="html-italic">p</span> < 0.001; **** <span class="html-italic">p</span> < 0.0001).</p> "> Figure 2
<p>PD-L1 expression and effect of PD-L1 intracellular signaling on cell proliferation of murine BCa cells. (<b>A</b>) Expression of PD-L1 in murine BCa cell lines analyzed by RT-qPCR. The fold change was relative to the expression of R221A. (<b>B</b>–<b>D</b>) Effect of SAM and anti-PD-L1 antibody on proliferation of murine BCa cells. (<b>B</b>) Eo771 (4 × 10<sup>4</sup>), (<b>C</b>) R221A (1 × 10<sup>4</sup>), and (<b>D</b>) EMT6 (4 × 10<sup>4</sup>) cells were seeded in 6-well plates and were added to rPD-1 (0.2 μg/mL, day 3). The cells were treated with either control (only rPD-1), SAM (200 μM, day 2, 3, 4), anti-PD-L1 antibody (50 μg/mL, day 4), or SAM and anti-PD-L1 in combination. The results are the mean of at least three independent experiments. Proliferation is represented as the percentage proportional to the control (± SEM). Statistical significance was determined by one-way ANOVA in GraphPad prism. Significance values are represented by asterisks (ns; not significant; *** <span class="html-italic">p</span> < 0.001; **** <span class="html-italic">p</span> < 0.0001).</p> "> Figure 3
<p>SAM, anti-PD-1 antibody, and the combination treatment decreased primary tumor growth in Eo771 tumor-bearing mice. (<b>A</b>) Eo771 (2 × 10<sup>5</sup> cells) were injected at the 4th m.f.p in B6 mice to induce tumor formation. The animals were treated with either the control (isotype matched IgG and PBS), SAM (80 mg/kg/day), anti-PD-1 antibody (5 mg/kg, twice per week), or combination. Tumor volumes were assessed at day 8, 15, and 20, and the animals were sacrificed at day 20. Results are presented as the mean ± SEM of tumor volume (<span class="html-italic">n</span> ≥ 7/group). (<b>B</b>) Percentage tumor growth inhibition (TGI) was calculated from tumor volumes at day 15 to day 20, relative to the control. (<b>C</b>) Tumor weight (mg ± SEM) was measured after tumor harvest on day 20. (<b>D</b>) Body weight (g ± SEM) of the mice was measured once a week. Statistical significance was determined by (<b>A</b>, <b>D</b>) two-way ANOVA; (<b>B</b>, <b>C</b>) one-way ANOVA in GraphPad prism. Significance values are represented by asterisks (ns, not significant; <span class="html-italic">* p</span> < 0.05; ** <span class="html-italic">p</span> < 0.01; *** <span class="html-italic">p</span> < 0.001 and **** <span class="html-italic">p</span> < 0.0001).</p> "> Figure 4
<p>SAM, anti-PD-1 antibody, and the combination treatment decreased lung metastasis in Eo771 tumor-bearing mice. Briefly, mice were injected with Eo771 cells orthotopically at the m.f.p and treated with the four treatments indicated. At the end of the study, lungs of the mice were harvested, fixed using formalin, embedded in paraffin, sliced, and stained with H&E. (<b>A</b>) Representative histology images of mouse lung showing the whole lung and magnified images to show metastatic lesions from each group except the SAM+anti-PD-1 antibody combination group, which had no lesions in this sample. Lens: top; 4×; bottom; 20×. Magnification: top; 40×; bottom; 200×. (<b>B</b>) Total metastatic lesion area (µm<sup>2</sup> ± SEM) for each group (<span class="html-italic">n</span> = 4/group). Total metastatic lesion area was calculated by annotating all the metastatic lesions in the entire lung of a mouse using the ImageScope annotation tool, which gives the selected area. Then, all the lesion areas were added together. (<b>C</b>) Percentage of mice with lung metastasis in each group. Statistical significance was determined by (B) one-way ANOVA in GraphPad prism. Significance values are represented by asterisks (<span class="html-italic">* p</span> < 0.05; ** <span class="html-italic">p</span> < 0.01).</p> "> Figure 5
<p>The SAM and anti-PD-1 antibody combination decreases bone metastasis and protects the bone from damage caused by aggressively growing tumor lesions. Briefly, mice were injected with Eo771 cells intra-tibially and treated with either control (isotype matched IgG and PBS, <span class="html-italic">n</span> = 10/group), SAM (80 mg/kg/day, <span class="html-italic">n</span> = 9/group), anti-PD-1 antibody (5 mg/kg, twice per week, <span class="html-italic">n</span> = 10/group), or the combination (<span class="html-italic">n</span> = 10/group). (<b>A</b>) Representative X-ray images showing the anatomy of the lower limb. The tibia, fibula, and femur (in part) along with the knee joint are shown. X-rays of the mice were taken at day 21 post-tumor injection. Black arrows indicate tumors, while white arrows indicate a broken cortical bone margin. (<b>B</b>) X-ray images were used to calculate a bone lesion score (BLS) for each group in increments from 0 to 4, where 0 represents no tumor lesions with the highest bone integrity (no breaks in the peripheral margin) and 4 represents the maximum tumor lesion area with the lowest bone integrity and with major breaks in the peripheral margin (<span class="html-italic">n</span> = 10/group, except SAM (<span class="html-italic">n</span> = 9/group)). (<b>C</b>) Representative histology images of mouse tibias 21 days post-tumor injection. Briefly, mice were sacrificed at day 21, and tibias were extracted, fixed, decalcified, embedded, sliced, and subjected to H&E staining, as described in Materials and Methods. T, tumor; BM, bone marrow. The black bar at the bottom left represents the scale in each image: top, 2 mm; below, 500 µm. (<b>D</b>) Total bone lesion area (µm<sup>2</sup>) for each group (<span class="html-italic">n</span> = 5/group). Briefly, the tumor lesion area in the whole tibia image was measured using the ImageScope annotation tool, added and plotted in GraphPad Prism. (<b>E</b>) Percentage of mice with bone metastasis in each group. Statistical significance was determined by (<b>B</b>, <b>D</b>) one-way ANOVA in GraphPad prism. Significance values are represented by asterisks (<span class="html-italic">* p</span> < 0.05; ** <span class="html-italic">p</span> < 0.01; **** <span class="html-italic">p</span> < 0.0001).</p> "> Figure 6
<p>Tumors treated with the SAM and anti-PD-1 antibody combination show reduced expression of key oncogenes and pro-metastasis genes, and elevated expression of immunostimulatory genes. (<b>A</b>) Venn diagram (left) and MA plot (right) showing significant DEGs (<span class="html-italic">p</span> < 0.001) in SAM and anti-PD-1 antibody combination-treated Eo771 tumors versus control Eo771 tumors. Up, upregulated genes; down, downregulated genes. (<b>B</b>) Change in expression of significantly downregulated genes in the combination-treated versus control tumors extracted from RNA-seq data (left, <span class="html-italic">n</span> = 3/group) and validated with RT-qPCR (right, <span class="html-italic">n</span> = 4/group). The data are presented as fold change in expression in the treatment group relative to the control. The value of the control was set at 1. (<b>C</b>) Expression of key pro-metastatic genes <span class="html-italic">MMP9</span> and <span class="html-italic">MMP10</span> in human solid normal tissue and primary tumor tissue of breast cancer patients derived from GTEx and TCGA databases (<span class="html-italic">n</span> = 1391 samples) using the Xena platform. Expression values are depicted in RSEM, which is RNA-Seq by Expectation Maximization. (<b>D</b>) Change in expression of top significantly upregulated genes in combination-treated versus control tumors extracted from RNA-seq data (left, <span class="html-italic">n</span> = 3/group) and validated with RT-qPCR (right, <span class="html-italic">n</span> = 4/group). Data is presented as fold change in the treatment group relative to the control. The value of the control was set at 1. CTL, cytotoxic T lymphocytes; APM, antigen processing and presentation machinery. (<b>E</b>) Immunohistochemistry with CD8a<sup>+</sup> T cell marker staining of Eo771 tumors treated with the combination treatment and the controls. (<b>E</b>, left) Representative images (lens, 40×; magnification, 400×) of the primary Eo771 tumors stained with murine antibody against CD8a<sup>+</sup> marker (brown) from the control and SAM+anti-PD-1 antibody combination-treated tumors. The nuclei are stained blue and a CD8<sup>+</sup> T cell is indicated by a black arrow. Enlarged images at the bottom right show the absence and presence of CD8<sup>+</sup> T cells in the control and SAM+anti-PD-1 antibody group, respectively. (<b>E</b>, right) CD8a<sup>+</sup> T cell positive staining area percentage (<span class="html-italic">n</span> = 4 samples/group). Statistical significance was determined using (<b>C</b>,<b>E</b>) T-test in GraphPad prism and (<b>A</b>,<b>B</b>,<b>D</b>) by Wald test with BH FDR (<span class="html-italic">≤ 0.2</span>) correction. Significance values are represented by asterisks (<span class="html-italic">* p</span> < 0.05; ** <span class="html-italic">p</span> < 0.01; **** <span class="html-italic">p</span> < 0.0001).</p> ">
Abstract
:Simple Summary
Abstract
1. Introduction
2. Results
2.1. SAM Decreases Proliferation, Colony Formation, and Invasion of BCa Cell Lines
2.2. Blocking Programmed Death Ligand 1 (PD-L1) Intrinsic Signalling Has No Effect on Cell Proliferation of BCa Cell Lines
2.3. The SAM and Anti-PD-1 Antibody Combination Has a Superior Effect in Reducing Primary Breast Tumor Growth Compared to Monotherapies
2.4. The SAM and Anti-PD-1 Antibody Combination Decreases Lung Metastasis
2.5. The SAM and Anti-PD-1 Antibody Combination Blocks Bone Metastasis and Protects Bone from Tumor Osteolytic Damage
2.6. The SAM and Anti-PD-1 Antibody Combination Reduces Expression of Oncogenes While Elevating Expression of Immunostimulatory Genes, as well as CD8+ T Cell Infiltration and Activity
3. Discussion
4. Materials and Methods
4.1. Cell Lines
4.2. Proliferation, Soft Agar Colony Formation, and Invasion Assays
4.3. Animal Studies
4.4. RNA Extraction and Reverse Transcriptase Quantitative Real-Time PCR (RT-qPCR)
4.5. RNA-Sequencing (RNA-Seq) and Analysis
4.6. Intratibial Model for Skeletal Metastasis
4.7. Immunohistochemistry (IHC)
4.8. Statistical Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Brenner, D.R.; Weir, H.K.; Demers, A.A.; Ellison, L.F.; Louzado, C.; Shaw, A.; Turner, D.; Woods, R.R.; Smith, L.M.; Canadian Cancer Statistics Advisory Committee. Projected estimates of cancer in Canada in 2020. CMAJ 2020, 192, E199–E205. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
- Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2017. Cancer J. Clin. 2018, 67, 7–30. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Seyfried, T.N.; Huysentruyt, L.C. On the origin of cancer metastasis. Crit. Rev. Oncog. 2013, 18, 43–73. [Google Scholar] [CrossRef] [Green Version]
- Chaffer, C.L.; Weinberg, R.A. A perspective on cancer cell metastasis. Science 2011, 331, 1559–1564. [Google Scholar] [CrossRef] [PubMed]
- Yersal, O.; Barutca, S. Biological subtypes of breast cancer: Prognostic and therapeutic implications. World J. Clin. Oncol. 2014, 5, 412–424. [Google Scholar] [CrossRef] [PubMed]
- Cardoso, F.; Kyriakides, S.; Ohno, S.; Penault-Llorca, F.; Poortmans, P.; Rubio, I.T.; Zackrisson, S.; Senkus, E.; on behalf of the ESMO Guidelines Committee. Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-updagger. Ann. Oncol. 2019, 30, 1194–1220. [Google Scholar] [CrossRef] [Green Version]
- Viale, G.; Hanlon Newell, A.E.; Walker, E.; Harlow, G.; Bai, I.; Russo, L.; Dell’Orto, P.; Maisonneuve, P. Ki-67 (30-9) scoring and differentiation of Luminal A- and Luminal B-like breast cancer subtypes. Breast Cancer Res. Treat. 2019, 178, 451–458. [Google Scholar] [CrossRef] [Green Version]
- Wu, Q.; Li, J.; Zhu, S.; Wu, J.; Chen, C.; Liu, Q.; Wei, W.; Zhang, Y.; Sun, S. Breast cancer subtypes predict the preferential site of distant metastases: A SEER based study. Oncotarget 2017, 8, 27990–27996. [Google Scholar] [CrossRef] [Green Version]
- Yang, M.; Liu, C.; Yu, X. Skeletal-related adverse events during bone metastasis of breast cancer: Current status. Discov. Med. 2019, 27, 211–220. [Google Scholar]
- Kane, C.M.; Hoskin, P.; Bennett, M.I. Cancer induced bone pain. BMJ 2015, 350, h315. [Google Scholar] [CrossRef] [PubMed]
- Harris, S.R. Differentiating the Causes of Spontaneous Rib Fracture After Breast Cancer. Clin. Breast Cancer 2016, 16, 431–436. [Google Scholar] [CrossRef] [PubMed]
- Alsaab, H.O.; Sau, S.; Alzhrani, R.; Tatiparti, K.; Bhise, K.; Kashaw, S.K.; Iyer, A.K. PD-1 and PD-L1 Checkpoint Signaling Inhibition for Cancer Immunotherapy: Mechanism, Combinations, and Clinical Outcome. Front. Pharmacol. 2017, 8, 561. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pardoll, D.M. The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer 2012, 12, 252. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schadendorf, D.; van Akkooi, A.C.J.; Berking, C.; Griewank, K.G.; Gutzmer, R.; Hauschild, A.; Stang, A.; Roesch, A.; Ugurel, S. Melanoma. Lancet 2018, 392, 971–984. [Google Scholar] [CrossRef] [PubMed]
- Kalbasi, A.; Ribas, A. Tumour-intrinsic resistance to immune checkpoint blockade. Nat. Rev. Immunol. 2020, 20, 25–39. [Google Scholar] [CrossRef]
- Barrueto, L.; Caminero, F.; Cash, L.; Makris, C.; Lamichhane, P.; Deshmukh, R.R. Resistance to Checkpoint Inhibition in Cancer Immunotherapy. Transl. Oncol. 2020, 13, 100738. [Google Scholar] [CrossRef]
- Alexandrov, L.B.; Nik-Zainal, S.; Wedge, D.C.; Aparicio, S.A.; Behjati, S.; Biankin, A.V.; Bignell, G.R.; Bolli, N.; Borg, A.; Borresen-Dale, A.L.; et al. Signatures of Mutational Processes in Human Cancer. Nature 2013, 500, 415–421. [Google Scholar] [CrossRef] [Green Version]
- Yarchoan, M.; Hopkins, A.; Jaffee, E.M. Tumor Mutational Burden and Response Rate to PD-1 Inhibition. N. Engl. J. Med. 2017, 377, 2500–2501. [Google Scholar] [CrossRef]
- Planes-Laine, G.; Rochigneux, P.; Bertucci, F.; Chretien, A.S.; Viens, P.; Sabatier, R.; Goncalves, A. PD-1/PD-L1 Targeting in Breast Cancer: The First Clinical Evidences Are Emerging. A Literature Review. Cancers 2019, 11, 1033. [Google Scholar] [CrossRef] [Green Version]
- Plitas, G.; Konopacki, C.; Wu, K.; Bos, P.D.; Morrow, M.; Putintseva, E.V.; Chudakov, D.M.; Rudensky, A.Y. Regulatory T Cells Exhibit Distinct Features in Human Breast Cancer. Immunity 2016, 45, 1122–1134. [Google Scholar] [CrossRef] [PubMed]
- Dieci, M.V.; Griguolo, G.; Miglietta, F.; Guarneri, V. The immune system and hormone-receptor positive breast cancer: Is it really a dead end? Cancer Treat. Rev. 2016, 46, 9–19. [Google Scholar] [CrossRef]
- Dieci, M.V.; Guarneri, V.; Tosi, A.; Bisagni, G.; Musolino, A.; Spazzapan, S.; Moretti, G.; Vernaci, G.M.; Griguolo, G.; Giarratano, T.; et al. Neoadjuvant Chemotherapy and Immunotherapy in Luminal B-like Breast Cancer: Results of the Phase II GIADA Trial. Clin. Cancer Res. 2022, 28, 308–317. [Google Scholar] [CrossRef]
- Miller, L.D.; Chou, J.A.; Black, M.A.; Print, C.; Chifman, J.; Alistar, A.; Putti, T.; Zhou, X.; Bedognetti, D.; Hendrickx, W.; et al. Immunogenic Subtypes of Breast Cancer Delineated by Gene Classifiers of Immune Responsiveness. Cancer Immunol. Res. 2016, 4, 600–610. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jung, H.; Kim, H.S.; Kim, J.Y.; Sun, J.M.; Ahn, J.S.; Ahn, M.J.; Park, K.; Esteller, M.; Lee, S.H.; Choi, J.K. DNA methylation loss promotes immune evasion of tumours with high mutation and copy number load. Nat. Commun. 2019, 10, 4278. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pakneshan, P.; Szyf, M.; Farias-Eisner, R.; Rabbani, S.A. Reversal of the hypomethylation status of urokinase (uPA) promoter blocks breast cancer growth and metastasis. J. Biol. Chem. 2004, 279, 31735–31744. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shukeir, N.; Pakneshan, P.; Chen, G.; Szyf, M.; Rabbani, S.A. Alteration of the methylation status of tumor-promoting genes decreases prostate cancer cell invasiveness and tumorigenesis in vitro and in vivo. Cancer Res. 2006, 66, 9202–9210. [Google Scholar] [CrossRef] [Green Version]
- Mahmood, N.; Cheishvili, D.; Arakelian, A.; Tanvir, I.; Khan, H.A.; Pepin, A.S.; Szyf, M.; Rabbani, S.A. Methyl donor S-adenosylmethionine (SAM) supplementation attenuates breast cancer growth, invasion, and metastasis in vivo; therapeutic and chemopreventive applications. Oncotarget 2018, 9, 5169–5183. [Google Scholar] [CrossRef] [Green Version]
- Mahmood, N.; Arakelian, A.; Cheishvili, D.; Szyf, M.; Rabbani, S.A. S-adenosylmethionine in combination with decitabine shows enhanced anti-cancer effects in repressing breast cancer growth and metastasis. J. Cell. Mol. Med. 2020, 24, 10322–10337. [Google Scholar] [CrossRef]
- Mahmood, N.; Arakelian, A.; Muller, W.J.; Szyf, M.; Rabbani, S.A. An enhanced chemopreventive effect of methyl donor S-adenosylmethionine in combination with 25-hydroxyvitamin D in blocking mammary tumor growth and metastasis. Bone Res. 2020, 8, 28. [Google Scholar] [CrossRef]
- Mahmood, N.; Rabbani, S.A. Targeting DNA Hypomethylation in Malignancy by Epigenetic Therapies. Adv. Exp. Med. Biol. 2019, 1164, 179–196. [Google Scholar] [CrossRef] [PubMed]
- Hote, P.T.; Sahoo, R.; Jani, T.S.; Ghare, S.S.; Chen, T.; Joshi-Barve, S.; McClain, C.J.; Barve, S.S. Ethanol inhibits methionine adenosyltransferase II activity and S-adenosylmethionine biosynthesis and enhances caspase-3-dependent cell death in T lymphocytes: Relevance to alcohol-induced immunosuppression. J. Nutr. Biochem. 2008, 19, 384–391. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tobena, R.; Horikawa, S.; Calvo, V.; Alemany, S. Interleukin-2 induces gamma-S-adenosyl-L-methionine synthetase gene expression during T-lymphocyte activation. Biochem. J. 1996, 319, 929–933. [Google Scholar] [CrossRef] [PubMed]
- LeGros, H.L., Jr.; Geller, A.M.; Kotb, M. Differential regulation of methionine adenosyltransferase in superantigen and mitogen stimulated human T lymphocytes. J. Biol. Chem. 1997, 272, 16040–16047. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kotb, M.; Dale, J.B.; Beachey, E.H. Stimulation of S-adenosylmethionine synthetase in human lymphocytes by streptococcal M protein. J. Immunol. 1987, 139, 202–206. [Google Scholar]
- De La Rosa, J.; Geller, A.M.; LeGros, H.L., Jr.; Kotb, M. Induction of interleukin 2 production but not methionine adenosyltransferase activity or S-adenosylmethionine turnover in Jurkat T-cells. Cancer Res. 1992, 52, 3361–3366. [Google Scholar]
- De La Rosa, J.; Kotb, M.; Kredich, N.M. Regulation of S-adenosylmethionine synthetase activity in cultured human lymphocytes. Biochim. Biophys. Acta 1991, 1077, 225–232. [Google Scholar] [CrossRef]
- German, D.C.; Bloch, C.A.; Kredich, N.M. Measurements of S-adenosylmethionine and L-homocysteine metabolism in cultured human lymphoid cells. J. Biol. Chem. 1983, 258, 10997–11003. [Google Scholar] [CrossRef]
- Zeng, Z.; Yang, H.; Huang, Z.Z.; Chen, C.; Wang, J.; Lu, S.C. The role of c-Myb in the up-regulation of methionine adenosyltransferase 2A expression in activated Jurkat cells. Biochem. J. 2001, 353, 163–168. [Google Scholar] [CrossRef]
- Kotb, M.; Kredich, N.M. S-Adenosylmethionine synthetase from human lymphocytes. Purification and characterization. J. Biol. Chem. 1985, 260, 3923–3930. [Google Scholar] [CrossRef]
- Sahin, E.; Sahin, M. Epigenetical Targeting of the FOXP3 Gene by S-Adenosylmethionine Diminishes the Suppressive Capacity of Regulatory T Cells Ex Vivo and Alters the Expression Profiles. J. Immunother. 2019, 42, 11–22. [Google Scholar] [CrossRef] [PubMed]
- Bian, Y.; Li, W.; Kremer, D.M.; Sajjakulnukit, P.; Li, S.; Crespo, J.; Nwosu, Z.C.; Zhang, L.; Czerwonka, A.; Pawlowska, A.; et al. Cancer SLC43A2 alters T cell methionine metabolism and histone methylation. Nature 2020, 585, 277–282. [Google Scholar] [CrossRef] [PubMed]
- Ulanovskaya, O.A.; Zuhl, A.M.; Cravatt, B.F. NNMT promotes epigenetic remodeling in cancer by creating a metabolic methylation sink. Nat. Chem. Biol. 2013, 9, 300–306. [Google Scholar] [CrossRef] [PubMed]
- Larroquette, M.; Domblides, C.; Lefort, F.; Lasserre, M.; Quivy, A.; Sionneau, B.; Bertolaso, P.; Gross-Goupil, M.; Ravaud, A.; Daste, A. Combining immune checkpoint inhibitors with chemotherapy in advanced solid tumours: A review. Eur. J. Cancer 2021, 158, 47–62. [Google Scholar] [CrossRef] [PubMed]
- Hanahan, D. Hallmarks of Cancer: New Dimensions. Cancer Discov. 2022, 12, 31–46. [Google Scholar] [CrossRef] [PubMed]
- Escors, D.; Gato-Cañas, M.; Zuazo, M.; Arasanz, H.; García-Granda, M.J.; Vera, R.; Kochan, G. The intracellular signalosome of PD-L1 in cancer cells. Signal Transduct. Target. Ther. 2018, 3, 26. [Google Scholar] [CrossRef] [Green Version]
- Dong, P.; Xiong, Y.; Yue, J.; Hanley, S.J.B.; Watari, H. Tumor-Intrinsic PD-L1 Signaling in Cancer Initiation, Development and Treatment: Beyond Immune Evasion. Front. Oncol. 2018, 8, 386. [Google Scholar] [CrossRef] [Green Version]
- Mehdi, A.; Attias, M.; Mahmood, N.; Arakelian, A.; Mihalcioiu, C.; Piccirillo, C.A.; Szyf, M.; Rabbani, S.A. Enhanced Anticancer Effect of a Combination of S-adenosylmethionine (SAM) and Immune Checkpoint Inhibitor (ICPi) in a Syngeneic Mouse Model of Advanced Melanoma. Front. Oncol. 2020, 10, 1361. [Google Scholar] [CrossRef]
- Le Naour, A.; Rossary, A.; Vasson, M.P. EO771, is it a well-characterized cell line for mouse mammary cancer model? Limit and uncertainty. Cancer Med. 2020, 9, 8074–8085. [Google Scholar] [CrossRef]
- Le Naour, A.; Koffi, Y.; Diab, M.; Le Guennec, D.; Rouge, S.; Aldekwer, S.; Goncalves-Mendes, N.; Talvas, J.; Farges, M.C.; Caldefie-Chezet, F.; et al. EO771, the first luminal B mammary cancer cell line from C57BL/6 mice. Cancer Cell. Int. 2020, 20, 328. [Google Scholar] [CrossRef]
- Gialeli, C.; Theocharis, A.D.; Karamanos, N.K. Roles of matrix metalloproteinases in cancer progression and their pharmacological targeting. FEBS J. 2011, 278, 16–27. [Google Scholar] [CrossRef] [PubMed]
- Jiang, H.; Li, H. Prognostic values of tumoral MMP2 and MMP9 overexpression in breast cancer: A systematic review and meta-analysis. BMC Cancer 2021, 21, 149. [Google Scholar] [CrossRef] [PubMed]
- Goldman, M.J.; Craft, B.; Hastie, M.; Repecka, K.; McDade, F.; Kamath, A.; Banerjee, A.; Luo, Y.; Rogers, D.; Brooks, A.N.; et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat. Biotechnol. 2020, 38, 675–678. [Google Scholar] [CrossRef] [PubMed]
- Zhang, M.; Fujiwara, K.; Che, X.; Zheng, S.; Zheng, L. DNA methylation in the tumor microenvironment. J. Zhejiang Univ. Sci. B 2017, 18, 365–372. [Google Scholar] [CrossRef] [Green Version]
- Ostrand-Rosenberg, S. Immune Surveillance: A Balance Between Pro- and Anti-tumor Immunity. Curr. Opin. Genet. Dev. 2008, 18, 11–18. [Google Scholar] [CrossRef] [Green Version]
- Sukari, A.; Nagasaka, M.; Al-Hadidi, A.; Lum, L.G. Cancer Immunology and Immunotherapy. Anticancer Res. 2016, 36, 5593–5606. [Google Scholar] [CrossRef]
- Gibney, G.T.; Weiner, L.M.; Atkins, M.B. Predictive biomarkers for checkpoint inhibitor-based immunotherapy. Lancet Oncol. 2016, 17, e542–e551. [Google Scholar] [CrossRef] [Green Version]
- Ji, R.R.; Chasalow, S.D.; Wang, L.; Hamid, O.; Schmidt, H.; Cogswell, J.; Alaparthy, S.; Berman, D.; Jure-Kunkel, M.; Siemers, N.O.; et al. An immune-active tumor microenvironment favors clinical response to ipilimumab. Cancer Immunol. Immunother. 2012, 61, 1019–1031. [Google Scholar] [CrossRef]
- Ilisso, C.P.; Sapio, L.; Delle Cave, D.; Illiano, M.; Spina, A.; Cacciapuoti, G.; Naviglio, S.; Porcelli, M. S-Adenosylmethionine Affects ERK1/2 and Stat3 Pathways and Induces Apotosis in Osteosarcoma Cells. J. Cell. Physiol. 2016, 231, 428–435. [Google Scholar] [CrossRef]
- Ilisso, C.P.; Delle Cave, D.; Mosca, L.; Pagano, M.; Coppola, A.; Mele, L.; Caraglia, M.; Cacciapuoti, G.; Porcelli, M. S-Adenosylmethionine regulates apoptosis and autophagy in MCF-7 breast cancer cells through the modulation of specific microRNAs. Cancer Cell. Int. 2018, 18, 197. [Google Scholar] [CrossRef]
- Cave, D.D.; Desiderio, V.; Mosca, L.; Ilisso, C.P.; Mele, L.; Caraglia, M.; Cacciapuoti, G.; Porcelli, M. S-Adenosylmethionine-mediated apoptosis is potentiated by autophagy inhibition induced by chloroquine in human breast cancer cells. J. Cell. Physiol. 2018, 233, 1370–1383. [Google Scholar] [CrossRef] [PubMed]
- Parashar, S.; Cheishvili, D.; Arakelian, A.; Hussain, Z.; Tanvir, I.; Khan, H.A.; Szyf, M.; Rabbani, S.A. S-adenosylmethionine blocks osteosarcoma cells proliferation and invasion in vitro and tumor metastasis in vivo: Therapeutic and diagnostic clinical applications. Cancer Med. 2015, 4, 732–744. [Google Scholar] [CrossRef] [PubMed]
- Shukeir, N.; Stefanska, B.; Parashar, S.; Chik, F.; Arakelian, A.; Szyf, M.; Rabbani, S.A. Pharmacological methyl group donors block skeletal metastasis in vitro and in vivo. Br. J. Pharmacol. 2015, 172, 2769–2781. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Bi, T.; Yuan, F.; Gao, X.; Jia, G.; Tian, Z. S-adenosylmethionine induces apoptosis and cycle arrest of gallbladder carcinoma cells by suppression of JAK2/STAT3 pathways. Naunyn Schmiedebergs Arch. Pharmacol. 2020, 393, 2507–2515. [Google Scholar] [CrossRef] [PubMed]
- Stagg, J.; Divisekera, U.; McLaughlin, N.; Sharkey, J.; Pommey, S.; Denoyer, D.; Dwyer, K.M.; Smyth, M.J. Anti-CD73 antibody therapy inhibits breast tumor growth and metastasis. Proc. Natl. Acad. Sci. USA 2010, 107, 1547–1552. [Google Scholar] [CrossRef] [Green Version]
- Hoover, R.G.; Gullickson, G.; Kornbluth, J. Natural killer lytic-associated molecule plays a role in controlling tumor dissemination and metastasis. Front. Immunol. 2012, 3, 393. [Google Scholar] [CrossRef] [Green Version]
- Singh, G.; Rabbani, A.S. Bone Metastasis; Human Press Inc.: Totowa, NJ, USA, 2005. [Google Scholar]
- Sun, X.; Li, K.; Hase, M.; Zha, R.; Feng, Y.; Li, B.Y.; Yokota, H. Suppression of breast cancer-associated bone loss with osteoblast proteomes via Hsp90ab1/moesin-mediated inhibition of TGFbeta/FN1/CD44 signaling. Theranostics 2022, 12, 929–943. [Google Scholar] [CrossRef]
- Feng, Y.; Liu, S.; Zha, R.; Sun, X.; Li, K.; Robling, A.; Li, B.; Yokota, H. Mechanical Loading-Driven Tumor Suppression Is Mediated by Lrp5-Dependent and Independent Mechanisms. Cancers 2021, 13, 267. [Google Scholar] [CrossRef]
- Pakneshan, P.; Tetu, B.; Rabbani, S.A. Demethylation of urokinase promoter as a prognostic marker in patients with breast carcinoma. Clin. Cancer Res. 2004, 10, 3035–3041. [Google Scholar] [CrossRef] [Green Version]
- Beatty, G.L.; Gladney, W.L. Immune escape mechanisms as a guide for cancer immunotherapy. Clin. Cancer Res. 2015, 21, 687–692. [Google Scholar] [CrossRef] [Green Version]
- Mehdi, A.; Rabbani, S.A. Role of Methylation in Pro- and Anti-Cancer Immunity. Cancers 2021, 13, 545. [Google Scholar] [CrossRef] [PubMed]
- Hung, M.H.; Lee, J.S.; Ma, C.; Diggs, L.P.; Heinrich, S.; Chang, C.W.; Ma, L.; Forgues, M.; Budhu, A.; Chaisaingmongkol, J.; et al. Tumor methionine metabolism drives T-cell exhaustion in hepatocellular carcinoma. Nat. Commun. 2021, 12, 1455. [Google Scholar] [CrossRef] [PubMed]
- Chik, F.; Machnes, Z.; Szyf, M. Synergistic anti-breast cancer effect of a combined treatment with the methyl donor S-adenosyl methionine and the DNA methylation inhibitor 5-aza-2’-deoxycytidine. Carcinogenesis 2014, 35, 138–144. [Google Scholar] [CrossRef] [PubMed]
- Shukeir, N.; Arakelian, A.; Chen, G.; Garde, S.; Ruiz, M.; Panchal, C.; Rabbani, S.A. A synthetic 15-mer peptide (PCK3145) derived from prostate secretory protein can reduce tumor growth, experimental skeletal metastases, and malignancy-associated hypercalcemia. Cancer Res. 2004, 64, 5370–5377. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Black, M.; Barsoum, I.B.; Truesdell, P.; Cotechini, T.; Macdonald-Goodfellow, S.K.; Petroff, M.; Siemens, D.R.; Koti, M.; Craig, A.W.; Graham, C.H. Activation of the PD-1/PD-L1 immune checkpoint confers tumor cell chemoresistance associated with increased metastasis. Oncotarget 2016, 7, 10557–10567. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bernardo, M.; Tolstykh, T.; Zhang, Y.A.; Bangari, D.S.; Cao, H.; Heyl, K.A.; Lee, J.S.; Malkova, N.V.; Malley, K.; Marquez, E.; et al. An experimental model of anti-PD-1 resistance exhibits activation of TGFss and Notch pathways and is sensitive to local mRNA immunotherapy. Oncoimmunology 2021, 10, 1881268. [Google Scholar] [CrossRef]
- Bourgeois-Daigneault, M.C.; Roy, D.G.; Aitken, A.S.; El Sayes, N.; Martin, N.T.; Varette, O.; Falls, T.; St-Germain, L.E.; Pelin, A.; Lichty, B.D.; et al. Neoadjuvant oncolytic virotherapy before surgery sensitizes triple-negative breast cancer to immune checkpoint therapy. Sci. Transl. Med. 2018, 10. [Google Scholar] [CrossRef] [Green Version]
- Gao, M.; Wang, T.; Ji, L.; Bai, S.; Tian, L.; Song, H. Therapy with Carboplatin and Anti-PD-1 Antibodies Before Surgery Demonstrates Sustainable Anti-Tumor Effects for Secondary Cancers in Mice With Triple-Negative Breast Cancer. Front. Immunol. 2020, 11, 366. [Google Scholar] [CrossRef] [Green Version]
- Rastelli, L.; Valentino, M.L.; Minderman, M.C.; Landin, J.; Malyankar, U.M.; Lescoe, M.K.; Kitson, R.; Brunson, K.; Souan, L.; Forenza, S.; et al. A KDR-binding peptide (ST100,059) can block angiogenesis, melanoma tumor growth and metastasis in vitro and in vivo. Int. J. Oncol. 2011, 39, 401–408. [Google Scholar] [CrossRef] [Green Version]
- Rabbani, S.A.; Ateeq, B.; Arakelian, A.; Valentino, M.L.; Shaw, D.E.; Dauffenbach, L.M.; Kerfoot, C.A.; Mazar, A.P. An anti-urokinase plasminogen activator receptor antibody (ATN-658) blocks prostate cancer invasion, migration, growth, and experimental skeletal metastasis in vitro and in vivo. Neoplasia 2010, 12, 778–788. [Google Scholar] [CrossRef] [Green Version]
- Yang, M.; Burton, D.W.; Geller, J.; Hillegonds, D.J.; Hastings, R.H.; Deftos, L.J.; Hoffman, R.M. The bisphosphonate olpadronate inhibits skeletal prostate cancer progression in a green fluorescent protein nude mouse model. Clin. Cancer Res. 2006, 12, 2602–2606. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rabbani, S.A.; Arakelian, A.; Farookhi, R. LRP5 knockdown: Effect on prostate cancer invasion growth and skeletal metastasis in vitro and in vivo. Cancer Med. 2013, 2, 625–635. [Google Scholar] [CrossRef] [PubMed]
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Mehdi, A.; Attias, M.; Arakelian, A.; Piccirillo, C.A.; Szyf, M.; Rabbani, S.A. Co-Targeting Luminal B Breast Cancer with S-Adenosylmethionine and Immune Checkpoint Inhibitor Reduces Primary Tumor Growth and Progression, and Metastasis to Lungs and Bone. Cancers 2023, 15, 48. https://doi.org/10.3390/cancers15010048
Mehdi A, Attias M, Arakelian A, Piccirillo CA, Szyf M, Rabbani SA. Co-Targeting Luminal B Breast Cancer with S-Adenosylmethionine and Immune Checkpoint Inhibitor Reduces Primary Tumor Growth and Progression, and Metastasis to Lungs and Bone. Cancers. 2023; 15(1):48. https://doi.org/10.3390/cancers15010048
Chicago/Turabian StyleMehdi, Ali, Mikhael Attias, Ani Arakelian, Ciriaco A. Piccirillo, Moshe Szyf, and Shafaat A. Rabbani. 2023. "Co-Targeting Luminal B Breast Cancer with S-Adenosylmethionine and Immune Checkpoint Inhibitor Reduces Primary Tumor Growth and Progression, and Metastasis to Lungs and Bone" Cancers 15, no. 1: 48. https://doi.org/10.3390/cancers15010048
APA StyleMehdi, A., Attias, M., Arakelian, A., Piccirillo, C. A., Szyf, M., & Rabbani, S. A. (2023). Co-Targeting Luminal B Breast Cancer with S-Adenosylmethionine and Immune Checkpoint Inhibitor Reduces Primary Tumor Growth and Progression, and Metastasis to Lungs and Bone. Cancers, 15(1), 48. https://doi.org/10.3390/cancers15010048